Data Science


Data science addresses emerging challenges in agriculture, migration, poverty, and other socioeconomic issues by using technologies like artifical intelligence and remote sensing to analyze large datasets. It helps in decision-making by enabling the development of more effective policies and solutions for sustainable development

Introduction to Data Science 
Data science addresses socioeconomic and development issues and challenges by using technologies like  machine learning, artificial intelligence and remote sensing to analyze large datasets. These techniques and technologies leverage big data or non-traditional data sources, to provide valuable insights for policymakers and stakeholders to make informed decisions for effective policies and solutions for sustainable development.

Data Science at ADB 
ADB, through the ERDD, contributes to addressing challenges in environment, biodiversity, climate, migration, poverty, and other socioeconomic issues by leveraging data science in research, indicator monitoring, knowledge generation, and capacity building of its partners and clients in developing member countries. 

    Available online courses on the use of remote sensing


    QGIS Online Course on Agricultural Statistics
    This course will: (i) introduce the learners to the fundamentals of geographic information system (GIS), basic spatial data concepts, and data types; (ii) train learners on the functionalities of QGIS; and (iii) use QGIS for agricultural data collection, mapping, and subsequent data analysis.

    Big Data Analytics in Agriculture and Seaports


    This SSTA analyzes climate change impacts on agriculture and food security, and assesses human activities (e.g., seaport development) on coastal environments. Using data modeling and non-traditional data sources, it will develop agricultural adaptation strategies and identify coastal water quality indicators. The findings will support policymakers in addressing climate and ocean health challenges. Aligned with ADB’s climate goals, this research aims to enhance sustainability in DMCs.

    Super-resolution Satellite Imagery as a Regional Public Good for Sustainable Development


    The TA will generate knowledge to: (i) develop a regional public good comprising an open-source method of deriving high-resolution (super- resolved) satellite imagery, and (ii) demonstrate how these images can be used to assess policy- relevant use-cases such as monitoring the green transition over time or assessing the quality of infrastructure

    Leveraging Big Data for Inclusive Policy Development: Alternative Tools for Monitoring Vulnerable Populations


    This TA explores how novel Big Data sources—including mobile location data, satellite imagery, and sensor devices—can serve as alternative policy tools to monitor vulnerable groups with greater precision. By disaggregating statistics and findings along socioeconomic (SES) levels, we aim to uncover disparities and inform targeted interventions. Applications include public health tracking via wearable devices, estimating tourism and migration flows, assessing displacement due to natural disasters (e.g., floods), and analyzing labor force transitions across industries.

    To uphold ethical standards, all data access will be mediated through owners, with strict protocols for anonymization and informed consent. The project will deliver policy-relevant methodologies and recommendations designed to strengthen the capacity of Developing Member Countries in harnessing Big Data for equitable decision-making—while balancing innovation with privacy protection.

    About Key Indicators

    For more than 50 years, Key Indicators for Asia and the Pacific has presented the latest data on economic, financial, social, and environmental development issues across Asia and the Pacific. It continues to act as a vital resource of data and statistics for policymakers, development practitioners, government officials, researchers, and students around the world.
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